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A data-driven forecasting strategy to predict continuous hourly energy demand in smart buildings
(2021)
Smart buildings seek to have a balance between energy consumption and occupant com-fort. To make this possible, smart buildings need to be able to foresee sudden changes in the build-ing’s energy consumption. With the help ...
Comparative study of continuous hourly energy consumption forecasting strategies with small data sets to support demand management decisions in buildings
(2022)
Buildings are one of the largest consumers of electrical energy, making it important to develop different strategies to help to reduce electricity consumption. Building energy consumption forecasting strategies are widely ...
Forecasting energy time-series data using a fuzzy ARTMAP neural network
(2020-10-14)
Time-series forecasting is an important field of machine learning and is fundamental in analyzing trends based on historical data from various sources. In this paper, a fuzzy ARTMAP neural network for time-series forecasting ...
Short‐term deterministic solar irradiance forecasting considering a heuristics‐based, operational approach
(MDPI, 2021)
Solar energy is an economic and clean power source subject to natural variability, while energy storage might attenuate it, ultimately, effective and operationally feasible forecasting techniques for energy management are ...
Evolutionary heuristic to determine future land use
(2008-09-29)
In the spatial electric load forecasting, the future land use determination is one of the most important tasks, and one of the most difficult, because of the stochastic nature of the city growth. This paper proposes a fast ...
Evolutionary heuristic to determine future land use
(2008-09-29)
In the spatial electric load forecasting, the future land use determination is one of the most important tasks, and one of the most difficult, because of the stochastic nature of the city growth. This paper proposes a fast ...
SALCER´s Project
SALCER (in Spanish: Sistema de Asesoramiento y
Localización de Centrales de EnergíaRenovables) could be
translated as Counseling and Location of Renewable Energy
Power Station´s System. Its objective is to develop a ...
Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption
(ELSEVIER SCIENCE SA, 2008)
There are several ways to attempt to model a building and its heat gains from external sources as well as internal ones in order to evaluate a proper operation, audit retrofit actions, and forecast energy consumption. ...
Fuzzy Time Series Methods Applied to Short -Term Photovoltaic Power Forecasting Forecasting
(, 2021)
Abstract— Solar photovoltaic energy has shown a significant growth in the last decade. In the face of this growth, there are challenges to consider for the high penetration rates of solar photovoltaic, since this type of ...